Researchers are finding a large number of potential applications for nano-particles in diverse field. For example, there is considerable interest in using nano-particles, particularly carbon structures, for medical applications, in batteries and fuel cells, and as coatings with desirable mechanical, thermal, electromagnetic, and/or optical properties, and for use in drilling and industrial polishing. Such carbon structures include, for example, carbon nano-tubes (“CNT”), and fullerenes, also known as “bucky balls,” such as C-60, C70, C76, and C84.
Nano-particles could be used as a component of a drug delivery system to deliver a drug, radiation, or other therapeutic agent to a targeted part of the body. For these applications the size of the nano-particles is critical. Because applications that use nano-particles typically use large quantities of nano-particles, it is important to be able to characterize large groups, that is, populations of nano-particles.
While there are many known methods to manufacture CNTs, such as combustion methods and arc methods, it has been difficult to characterize the results of the manufacturing process to determine the size and other properties of the product of the manufacture. Current methods entail sampling and manually measuring individual nano-particles, for example, using a scanning electron microscope (SEM) or atomic force microscope (AFM). Such manual methods are slow and expensive, and are in fact economically prohibitive to commercial success of these technologies. Without an efficient way to characterize populations of nano-particles, it is difficult to control the manufacturing process to consistently produce the desired results. Moreover, statistical quality control will be required for almost any application of nano-particles, and is particularly important in medical applications, such as drug delivery systems. Without an efficient way to characterize populations of nano-particles, their practical applications will be limited.